Faculty Bibliography

A large number of studies have examined the association between advanced paternal age (APA) and risk of schizophrenia in offspring. Here we present an overview of epidemiological studies on this subject published since 2000, and systematically summarize their methodologies and results. Next, we discuss evidence to elucidate the potential mechanisms contributing to the association between APA and offspring schizophrenia, considering paternal psychiatric morbidity and genetic liability, maternal factors, and findings from family design studies. We propose that multiple mechanisms, including causal and non-causal pathways, contribute to the observed relationship between APA and schizophrenia in offspring, and conclude by highlighting the need for multi-disciplinary studies in disentangling these complex, non-mutually exclusive mechanisms.

Inherited monoamine neurotransmitter disorders (iMNDs) are rare disorders with clinical manifestations ranging from mild infantile hypotonia, movement disorders to early infantile severe encephalopathy. Neuroimaging has been reported as non-specific. We systematically analyzed brain MRIs in order to characterize and better understand neuroimaging changes and to re-evaluate the diagnostic role of brain MRI in iMNDs. 81 MRIs of 70 patients (0.1-52.9 years, 39 patients with tetrahydrobiopterin deficiencies, 31 with primary disorders of monoamine metabolism) were retrospectively analyzed and clinical records reviewed. 33/70 patients had MRI changes, most commonly atrophy (n = 24). Eight patients, six with dihydropteridine reductase deficiency (DHPR), had a common pattern of bilateral parieto-occipital and to a lesser extent frontal and/or cerebellar changes in arterial watershed zones. Two patients imaged after acute severe encephalopathy had signs of profound hypoxic-ischemic injury and a combination of deep gray matter and watershed injury (aromatic l-amino acid decarboxylase (AADCD), tyrosine hydroxylase deficiency (THD)). Four patients had myelination delay (AADCD; THD); two had changes characteristic of post-infantile onset neuronal disease (AADCD, monoamine oxidase A deficiency), and nine T2-hyperintensity of central tegmental tracts. iMNDs are associated with MRI patterns consistent with chronic effects of a neuronal disorder and signs of repetitive injury to cerebral and cerebellar watershed areas, in particular in DHPRD. These will be helpful in the (neuroradiological) differential diagnosis of children with unknown disorders and monitoring of iMNDs. We hypothesize that deficiency of catecholamines and/or tetrahydrobiopterin increase the incidence of and the CNS susceptibility to vascular dysfunction.

The United States is the only high-income country that does not have a national policy mandating paid leave to working women who give birth. Increased rates of maternal employment post-birth call for greater understanding of the effects of family leave on infant development. This study examined the links between paid leave and toddler language, cognitive, and socioemotional outcomes (24-36 months; N = 328). Results indicate that paid leave was associated with better language outcomes, regardless of socioeconomic status. Additionally, paid leave was correlated with fewer infant behavior problems for mothers with lower levels of educational attainment. Expanding access to policies that support families in need, like paid family leave, may aid in reducing socioeconomic disparities in infant development.

Pre-mobile infants and caregivers spontaneously engage in a sequence of contingent facial expressions and vocalizations that researchers have referred to as a social "dance." Does this dance continue when both partners are free to move across the floor? Locomotor synchrony was assessed in 13- to 19-month-old infant-mother dyads (N = 30) by tracking each partner's step-to-step location during free play. Although infants moved more than mothers, dyads spontaneously synchronized their locomotor activity. For 27 dyads, the spatiotemporal path of one partner uniquely identified the path of the other. Clustering analyses revealed two patterns of synchrony (mother-follow and yo-yo), and infants were more likely than mothers to lead the dance. Like face-to-face synchrony, locomotor synchrony scaffolds infants' interactions with the outside world.

Rhythms of the brain are generated by neural oscillations across multiple frequencies. These oscillations can be decomposed into distinct frequency intervals associated with specific physiological processes. In practice, the number and ranges of decodable frequency intervals are determined by sampling parameters, often ignored by researchers. To improve the situation, we report on an open toolbox with a graphical user interface for decoding rhythms of the brain system (DREAM). We provide worked examples of DREAM to investigate frequency-specific performance of both neural (spontaneous brain activity) and neurobehavioral (in-scanner head motion) oscillations. DREAM decoded the head motion oscillations and uncovered that younger children moved their heads more than older children across all five frequency intervals whereas boys moved more than girls in the age of 7 to 9 years. It is interesting that the higher frequency bands contain more head movements, and showed stronger age-motion associations but weaker sex-motion interactions. Using data from the Human Connectome Project, DREAM mapped the amplitude of these neural oscillations into multiple frequency bands and evaluated their test-retest reliability. The resting-state brain ranks its spontaneous oscillation's amplitudes spatially from high in ventral-temporal areas to low in ventral-occipital areas when the frequency band increased from low to high, while those in part of parietal and ventral frontal regions are reversed. The higher frequency bands exhibited more reliable amplitude measurements, implying more inter-individual variability of the amplitudes for the higher frequency bands. In summary, DREAM adds a reliable and valid tool to mapping human brain function from a multiple-frequency window into brain waves.

BACKGROUND:We analyzed the relationship between the prevalence of schizophrenia and the season of birth and gestation during a period of an influenza pandemic. METHODS:Cross-sectional analysis of a prospective population-based cohort of 470,942 adults. We fitted multivariant logistic regression models to determine whether the season of birth and birth in an influenza-pandemic year (1957, 1968, 1977) was associated with schizophrenia. RESULTS:2077 subjects had been diagnosed with schizophrenia. Logistic regression identified a significantly greater prevalence of schizophrenia in men than in women (OR = 1.516, CI 95% = 1.388-1.665); in those born in the winter or spring than in those born in the summer or autumn (OR = 1.112, CI 95% = 1.020-1.212); and in those born in a period of an influenza pandemic (OR = 1.335, CI 95% = 1.199-1.486). The increase in risk was also significant when each influenza pandemic year was analyzed separately. However, neither month of birth nor season of birth, when each of the four were studied individually, were associated with a statistically significant increase in that risk. CONCLUSIONS:The winter-spring period and the influenza pandemics are independent risk factors for developing schizophrenia. This study contradicts many previous studies and thus revitalizes a locked debate in understanding the neurodevelopmental hypothesis of this disorder.

OBJECTIVE/UNASSIGNED:There was no evidence that 90-days outcomes differed for veterans based on medication received, and there were more similarities than differences in clinical characteristics. Additional research is needed, including larger sample size and prospective randomized control trial to evaluate VA patients' treatment outcomes receiving BUP-NX or XR-NTX for OUD.

BACKGROUND:As mobile technologies become ever more sensor-rich, portable, and ubiquitous, data captured by smart devices are lending rich insights into users' daily lives with unprecedented comprehensiveness and ecological validity. A number of human-subject studies have been conducted to examine the use of mobile sensing to uncover individual behavioral patterns and health outcomes, yet minimal attention has been placed on measuring living environments together with other human-centered sensing data. Moreover, the participant sample size in most existing studies falls well below a few hundred, leaving questions open about the reliability of findings on the relations between mobile sensing signals and human outcomes. RESULTS:To address these limitations, we developed a home environment sensor kit for continuous indoor air quality tracking and deployed it in conjunction with smartphones, Fitbits, and ecological momentary assessments in a cohort study of up to 1,584 college student participants per data type for 3 weeks. We propose a conceptual framework that systematically organizes human-centric data modalities by their temporal coverage and spatial freedom. Then we report our study procedure, technologies and methods deployed, and descriptive statistics of the collected data that reflect the participants' mood, sleep, behavior, and living environment. CONCLUSIONS:We were able to collect from a large participant cohort satisfactorily complete multi-modal sensing and survey data in terms of both data continuity and participant adherence. Our novel data and conceptual development provide important guidance for data collection and hypothesis generation in future human-centered sensing studies.